Transcriptomic data for The Cancer Genome Atlas (TCGA)-LUAD cohort were obtained from TCGA portal (https://portal.gdc.cancer.gov) using the Spliced Transcripts Alignment to a Reference processing pipeline. Expression profiles were extracted in the transcripts per million format, and paired tumor-adjacent and tumor tissue samples were identified based on matched patient identifiers. In total, 598 samples were included in the analysis, comprising 59 normal lung tissues and 539 LUAD specimens.

Bioinformatics and statistical analyses were performed in R (v4.5.2; R Core Team; http://www.R-project.org/) (26). The expression levels of SCN4B in LUAD and adjacent normal tissues were compared using the ‘limma’ R package (v3.66.0; http://bioconductor.org/packages/release/bioc/html/limma.html). The log₂ fold change (log₂FC) and adjusted P-value (adj. P.Val) were calculated for all genes, and those with |log₂FC|>1 and adj. P.Val <0.05 were considered significantly differentially expressed. Receiver operating characteristic (ROC) curve analysis was performed using the ‘pROC’ package (v1.19.0.1; http://cran.r-project.org/package=pROC), and the results were visualized with ‘ggplot2’ (v4.0.1; http://cran.r-project.org/package=ggplot2) (27).

Boxplots were generated using the ‘ggplot2’ package to display SCN4B expression differences between tumor and normal lung tissues. Volcano plots were generated using the ‘ggplot2’ package to visualize SCN4B-associated differentially expressed genes between the SCN4B high- and low-expression groups within the TCGA-LUAD tumor cohort. Correlation heatmaps illustrating the relationships between SCN4B and selected lung cancer-associated marker genes were created to facilitate visualization of co-expression patterns (28).

SCN4B-associated differentially expressed genes identified between the SCN4B high- and low-expression groups within the TCGA-LUAD tumor cohort (|log₂FC|>1; adj. P.Val <0.05) were selected for enrichment analysis. GO annotation and KEGG pathway enrichment analysis were performed using the R package ‘clusterProfiler’ (v4.4.4; http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html) package (29), running under R (v4.5.2; R Core Team; http://www.R-project.org/). Bubble plots generated with the R package ‘ggplot2’ were used to present the enrichment results.

OS data for patients with LUAD were obtained from the Gene Expression Profiling Interactive Analysis 2 platform (v2.0; http://gepia2.cancer-pku.cn/#index), while disease-specific survival (DSS) and progression-free interval (PFI) information were sourced from TCGA. Kaplan-Meier survival analysis was conducted, and statistical differences were assessed using the log-rank test. Corresponding P-values were calculated and displayed on the survival plots (30).

In GSE31210 (GPL570), OS was used as the endpoint. SCN4B expression was extracted using probe 236359_at and patients were dichotomized at the cohort median to generate Kaplan-Meier curves and the number at risk table. Groups were compared using the two-sided log-rank test.

Clinical information for patients with LUAD, including age, sex, tumor stage and metastatic status, was retrieved from TCGA. The association between SCN4B expression and clinical characteristics (such as tumor stage and metastasis) was evaluated using either the χ² test or Fisher's exact test (32) (Table I). Bar plots illustrating the relationship between SCN4B expression and clinical features were generated with the ‘ggplot2’ package (33).

Correlations between SCN4B expression levels and immune cell infiltration scores were assessed, and the results were visualized using lollipop plots generated with the ‘ggplot2’ package.

The immunohistochemical expression patterns of SCN4B in adjacent non-tumor and LUAD tissues were obtained from the Human Protein Atlas (HPA) database (https://www.proteinatlas.org/). The analysis was conducted within the ‘Tissue’ section to explore potential biological implications of SCN4B in LUAD.

The human LUAD cell lines A549, NCI-H1299, NCI-H1975, PC-9 and HCC827, and the normal human bronchial epithelial cell line BEAS-2B (all from Wuhan Servicebio Technology Co., Ltd.), were maintained in a humidified incubator at 37°C with 5% CO₂. A549, NCI-H1299 and BEAS-2B cells were cultured in DMEM (Wuhan Servicebio Technology Co., Ltd.), whereas NCI-H1975, PC-9 and HCC827 cells were cultured in RPMI-1640 medium (Wuhan Servicebio Technology Co., Ltd.). All media were supplemented with 10% FBS (Wuhan Servicebio Technology Co., Ltd.) and 1% penicillin-streptomycin (Wuhan Servicebio Technology Co., Ltd.; final concentration 100 U/ml penicillin and 100 µg/ml streptomycin, 100X stock solution). The culture medium was refreshed every 48 h, and cells were passaged at 80–90% confluence (typically every 2–3 days). Cells were cryopreserved at −80°C overnight and then transferred to liquid nitrogen for long-term storage following standard procedures.

SCN4B overexpression plasmid DNA was transiently transfected into A549 and NCI-H1299 cells using Lipofectamine^® 3000 (Invitrogen; Thermo Fisher Scientific, Inc.). The SCN4B coding sequence was cloned into the pcDNA3.1(+) backbone at the BamHI/EcoRI sites (Sangon Biotech Co., Ltd.). Cells were seeded in 6-well plates (0.3–1×10⁵ cells/well) 1 day before transfection. On the day of transfection, 0.5 µg plasmid DNA and 1.5–2.5 µl Lipofectamine 3000 were prepared in serum-free DMEM (Wuhan Servicebio Technology Co., Ltd.) to form transfection complexes according to the manufacturer's instructions, which were then added to the cells. Cells were incubated at 37°C with 5% CO₂ for 18–24 h (without antibiotics). The transfection efficiency was validated by reverse transcription-quantitative PCR (RT-qPCR) to assess SCN4B mRNA expression. Cells were divided into two groups: Vector (empty plasmid) and oe-SCN4B (SCN4B overexpression). Subsequent experiments were initiated at 48 h post-transfection, unless otherwise stated.

Cells were seeded into 96-well plates at a density of 5×10³ cells/well and incubated at 37°C with 5% CO₂ to allow attachment. At 48 h post-transfection (defined as 0 h for the CCK-8 assay), and at 24, 48 and 72 h thereafter, 10 µl CCK-8 reagent (Wuhan Servicebio Technology Co., Ltd.) was added to each well containing 100 µl culture medium, and plates were incubated for 1–4 h. Absorbance was measured at 450 nm using a microplate reader to quantify the formazan product, which reflects cell viability.

For the invasion assay, Transwell inserts were precoated with Matrigel (Wuhan Servicebio Technology Co., Ltd.) at 37°C for 30 min prior to cell seeding. Cells were harvested and resuspended in serum-free DMEM, and a total of 5×10⁵ cells in 50 µl were seeded into the upper chamber of each Transwell insert, with the lower chamber filled with DMEM supplemented with 20% FBS (Wuhan Servicebio Technology Co., Ltd.). Each group was prepared in triplicate and cells were incubated at 37°C with 5% CO₂ for 48 h. Non-invaded cells on the upper surface were gently removed with cotton swabs. The inserts were fixed with 4% paraformaldehyde (Beyotime Biotechnology) for 15 min at room temperature (20–25°C), stained with crystal violet for 10 min at room temperature and washed three times with PBS. Invaded cells in five random fields (magnification, ×100) were imaged using an inverted light microscope and counted using ImageJ software (v1.52a; National Institutes of Health).

A549 and H1299 cells were seeded at 5×10⁵ cells/well in 6-well plates. Upon reaching ~97% confluence, a scratch was made using a 200-µl pipette tip guided by a ruler to maintain uniform width. Detached cells were removed by PBS washing, followed by incubation in low-serum medium (1% FBS). Images were captured at 0 and 48 h (34) at the same wound site using an inverted light microscope (magnification, ×100). The wound closure rate (%) was calculated as: Wound closure rate (%)=[(area at 0 h-area at 48 h)/area at 0 h] ×100. The wound area was quantified using ImageJ software (v1.52a; National Institutes of Health). All assays were repeated three times.

Total RNA was extracted from cells using TRIzol^® reagent (Beyotime Biotechnology) following the manufacturer's instructions. Briefly, cells at 70–80% confluence (~1×10⁶ cells per sample) were lysed in 1 ml TRIzol for RNA extraction. First-strand cDNA was synthesized from 1 µg total RNA using a first-strand cDNA synthesis kit (Beyotime Biotechnology) according to the manufacturer's protocol. qPCR was performed on a Rotor-Gene 3000 real-time PCR system (Gene Company, Ltd.) using SYBR^® Green qPCR Master Mix (Beyotime Biotechnology; the fluorophore was SYBR Green I dye provided in the master mix). Each reaction was carried out in a 20 µl volume, and amplification was performed with the following thermocycling conditions: 95°C for 30 sec, followed by 40 cycles of 95°C for 5 sec and 60°C for 30 sec; melt-curve analysis was performed to verify specificity. GAPDH served as the internal control, and relative expression levels were calculated using the 2^−ΔΔCq method (35). All qPCR reactions were performed in triplicate (technical replicates). The primer sequences for the target genes were as follows: SCN4B forward, 5′-TCTTCCTGCTCCCCGTAAC-3′ and reverse, 5′-AATGCGTCACTGCTGTTGTAG-3′; and GAPDH forward, 5′-CTGGGCTACACTGAGCACC-3′ and reverse, 5′-AAGTGGTCGTTGAGGGCAATG-3′.

Total cellular proteins were extracted from the collected cell pellets using pre-chilled RIPA lysis buffer (Beijing Solarbio Science & Technology Co., Ltd.) supplemented with protease and phosphatase inhibitors. Protein concentrations were determined via a BCA assay. A total of 30 µg protein was loaded per lane. Equal amounts of protein samples were separated on 10% SDS-PAGE gels and subsequently transferred onto PVDF membranes. After blocking with 5% non-fat milk at room temperature for 1 h, the membranes were incubated overnight at 4°C with primary antibodies against SCN4B (cat. no. DF4512; 1:1,000), E-cadherin (cat. no. BF0219; 1:1,000), N-cadherin (cat. no. AF5239; 1:1,000), Vimentin (cat. no. BF8006; 1:1,000), Snail (cat. no. AF6032; 1:1,000) and GAPDH (cat. no. AF7021; 1:1,000). Subsequently, the membranes were incubated for 2 h at room temperature with horseradish peroxidase-conjugated secondary antibodies corresponding to the species of the primary antibodies: Anti-rabbit IgG (cat. no. S0001; 1:10,000) or anti-mouse IgG (cat. no. S0002; 1:10,000). All primary and secondary antibodies were purchased from Affinity Biosciences. Protein bands were visualized using a SuperECL Plus chemiluminescent detection kit (LI-COR Biosciences) and imaged with the Bio-Rad ChemiDoc MP system (Bio-Rad Laboratories, Inc.). Band intensities were semi-quantified using ImageJ software (v1.5.2a; National Institutes of Health).

Cells were harvested, washed twice with cold PBS and resuspended in 1X Annexin V binding buffer (10 mM HEPES, 140 mM NaCl, 2.5 mM CaCl₂, pH 7.4) at ~1×10⁶ cells/ml. For each sample, 100 µl of cell suspension was incubated with 5 µl annexin V-FITC and 5 µl PI (Annexin V-FITC Apoptosis Detection Kit; cat. no. C1062; Beyotime Biotechnology) for 15 min at room temperature in the dark. After adding 400 µl binding buffer, samples were analyzed within 1 h on a CytoFLEX flow cytometer (Beckman Coulter, Inc.) using the FITC and PI channels. Data acquisition was performed with CytExpert software (v2.4; Beckman Coulter, Inc.), and data were analyzed with FlowJo (v10.10.0; BD Biosciences). Single-stained and unstained controls were used for compensation. Events were gated to exclude debris and doublets [forward scatter (FSC)/side scatter; FSC-area vs. FSC-height]. No fixation was performed prior to acquisition. Cells were classified as viable (annexin V⁻/PI⁻), early apoptotic (annexin V⁺/PI⁻), late apoptotic (annexin V⁺/PI⁺) or necrotic (annexin V⁻/PI⁺). The apoptosis rate (%) was calculated as early + late apoptosis.

Unless otherwise stated, all experiments were performed in triplicate. Data are presented as the mean ± SD from three independent experiments (n=3), unless otherwise indicated. For non-normally distributed continuous variables, data are presented as the median (interquartile range). Statistical analyses were conducted using GraphPad Prism 8.0 (Dotmatics) and SPSS 26.0 (IBM Corp.). Categorical clinicopathological variables were compared between high and low SCN4B expression groups using χ² tests or Fisher's exact tests. Survival was analyzed using the Kaplan-Meier method, and differences were evaluated using the log-rank test. For expression analyses based on transcriptomic data, paired data were analyzed using a paired Student's t-test, and unpaired comparisons with unequal variances were analyzed using Welch's t-test. Comparisons among multiple groups were performed using the Kruskal-Wallis test followed by Dunn's multiple comparisons test when data were not normally distributed, whereas two-group comparisons were performed using the Wilcoxon rank-sum test under the same conditions. Spearman's rank correlation was used to assess correlations between SCN4B expression and the expression of selected genes. A two-tailed unpaired Student's t-test was used to analyze the wound healing, Transwell and flow cytometry apoptosis assay data, as well as RT-qPCR (ΔCq values) and western blot densitometric semi-quantification data, comparing between the vector and oe-SCN4B groups. Baseline SCN4B expression across multiple lung adenocarcinoma cell lines was compared using one-way ANOVA with Dunnett's post hoc test. The CCK-8 assay data were analyzed using two-way ANOVA with Bonferroni's post hoc test. Correlations between SCN4B expression and immune cell infiltration scores were evaluated using Spearman correlation analysis, and the corresponding correlation coefficients and P-values are shown in the figures. ROC curves were generated to assess the diagnostic performance of SCN4B. P<0.05 was considered to indicate a statistically significant difference.

In TCGA-LUAD dataset, 539 tumor samples and 59 adjacent normal tissue samples were analyzed, and 58 matched tumor-normal pairs were available for paired analysis (Fig. 2A). The baseline clinical characteristics of patients with LUAD with high and low SCN4B expression are summarized in Table I. Elevated SCN4B expression was markedly associated with earlier T stage, sex, age and smoking status, whereas no significant differences were observed in N stage, M stage, overall pathological stage or anatomic neoplasm subdivision.

Expression profiling revealed that SCN4B was markedly downregulated in LUAD tissues compared with adjacent normal tissues (Fig. 2A). The external GEO cohort (GSE31210) exhibited significant downregulation of SCN4B in tumor vs. normal lung tissues (Fig. 2B). ROC curve analysis (Fig. 2C) indicated that SCN4B possessed strong diagnostic potential, with an area under the curve of 0.979 (95% CI, 0.969–0.990).

The volcano plot of SCN4B-associated differentially expressed genes between the SCN4B high- and low-expression groups is shown in Fig. 3A. Spearman's rank correlation analysis was performed to assess the correlation between SCN4B and several genes, including ADAMTS8, ADH1B, INMT, FHL1, C1QTNF7, MAMDC2, ATP1A2, TBX4, SCN7A, TCF21 and ITGA8 (Fig. 3B). These associations suggest that SCN4B and the identified genes may participate in common biological processes (BPs) or signaling pathways, potentially exerting cooperative or reciprocal regulatory effects.

GO functional enrichment analysis indicated that the SCN4B-associated differentially expressed genes were significantly enriched in BP terms including ‘cell-substrate adhesion’, ‘extracellular structure organization’, ‘extracellular matrix organization’ and ‘heart morphogenesis’. At the cellular component level, the SCN4B-associated differentially expressed genes were mainly associated with ‘collagen-containing extracellular matrix’, ‘cell-cell junction’, ‘caveola’ and ‘platelet alpha granule’. In terms of molecular functions (MFs), the SCN4B-associated differentially expressed genes were primarily enriched in ‘sulfur compound binding’, ‘glycosaminoglycan binding’, ‘heparin binding’ and ‘extracellular matrix structural constituent’ (Fig. 4A). In addition, KEGG pathway enrichment analysis showed that the SCN4B-associated differentially expressed genes were enriched in pathways such as ‘cell adhesion molecules’ (CAMs), ‘vascular smooth muscle contraction’, ‘dilated cardiomyopathy’, ‘hypertrophic cardiomyopathy’ and ‘arrhythmogenic right ventricular cardiomyopathy’ (Fig. 4B).

SCN4B expression was positively associated with mast cells, eosinophils and immature dendritic cells (iDCs). By contrast, SCN4B expression showed a negative correlation with type 2 helper T cells (Th2 cells), natural killer (NK) CD56^dim cells, γδ T cells (Tgds) and regulatory T cells (Tregs) (Fig. 5A).

As shown in Fig. 5B, SCN4B expression was negatively associated with tumor purity, and weak positive correlations were observed with M2 macrophage and NK cell infiltration levels estimated by quantification of the tumor immune contexture from RNA sequencing.

Analysis using the HPA database revealed that SCN4B expression was nearly absent in tumor tissues, whereas detectable expression was observed in adjacent non-tumor tissues (Fig. 6).

Patients with high SCN4B expression exhibited longer OS and DSS than those with low expression (Fig. 7A and B). High SCN4B expression was associated with a longer PFI (Fig. 7C).

In the analysis of SCN4B expression across TNM stages, a significant difference was observed between T1 and T2 stages, with markedly reduced expression in T2 tumors. SCN4B expression differed between stages T1 and T2. However, no statistically significant differences were observed in stage T3-T4 compared with stages T1 or T2 (Fig. 7D). Furthermore, SCN4B expression was not markedly associated with lymph node metastasis, distant metastasis or overall tumor stage (Fig. 7E-G).

In the external LUAD cohort GSE31210, high SCN4B expression was associated with improved survival. After median dichotomization, Kaplan-Meier curves and the ‘number at risk’ table displayed below the plot showed a significant difference between groups (Fig. 8).

First, SCN4B protein and mRNA levels were screened by western blotting and RT-qPCR in a normal lung-derived cell line and multiple lung cancer cell lines. Using the normal cell line as the reference and normalizing to GAPDH, most cancer cell lines exhibited a marked reduction in SCN4B signal. The decrease was most consistent and pronounced in A549 and H1299 cells, which were therefore selected for subsequent functional assays (Fig. 9).

SCN4B overexpression cell lines were established in A549 and H1299 cells by transfection with an overexpression plasmid. The results showed that the mRNA expression levels of SCN4B were markedly increased in the oe-SCN4B group compared with the vector group (Fig. 10).

The CCK-8 assay results demonstrated that SCN4B overexpression markedly reduced the viability of A549 and H1299 cells in a time-dependent manner, with prolonged exposure leading to stronger inhibitory effects (Fig. 11A).

Flow cytometry analysis using annexin V-FITC/PI double staining revealed that SCN4B overexpression markedly increased the proportion of apoptotic cells (early apoptosis + late apoptosis) in A549 and H1299 LUAD cells (Fig. 11B and C).

Transwell assay results showed that the number of invasive cells was significantly decreased following SCN4B overexpression (Fig. 12A). In addition, wound healing assay results indicated that SCN4B overexpression markedly slowed the wound closure rate and markedly reduced the healing area compared with the vector group (Fig. 12B).

Western blot analysis revealed that SCN4B overexpression markedly increased the relative expression levels of E-cadherin, while suppressing the relative expression levels of N-cadherin, Vimentin and Snail (Fig. 13).